How to apply Cycle Theory on Forex?
Greetings, friends forex traders!
Most technical analysis tools see prices as their main starting point. But any trading instrument has one more characteristic. This time.
Of course, any technical analysis tool takes into account time as well, but its significance is simply implied. Today we look at time as the main analysis tool. A rather philosophical theme of time and its application in trade awaits you.
We will talk about the so-called cycles. Specialists engaged in such an analysis believe that only cyclicality as a feature of market development is an explanation of the ups and downs of prices. We will supplement the list of the most important technical tools for market analysis with a temporary parameter and we can answer not only the question in which direction and how far the market will develop, but also when it will come there and when this movement will begin.
Let's look at the usual daily chart of the EURUSD pair. The vertical axis is the price scale. This indicator gives us only half of the necessary picture. The horizontal axis is the time scale. Thus, the chart is actually a graph not only of price but also of time. However, many traders analyze exclusively price data, completely ignoring the time factor.
When we study graphic models, we understand that there is a connection between the time for which this or that configuration is formed, and the potential of further market movement. The longer the trend lines “hold” or the levels of support or resistance, the more significant they become. The time factor is also very important when using the moving average as an analytical tool, for which it is very important to choose the appropriate time period. Even when working with oscillators, you have to make a decision regarding the number of days that make up the calculation period.
It becomes clear that any method of technical analysis to one degree or another depends on the time factor. At the same time, the use of time indicators is not always consistent. To increase the effectiveness of technical analysis, taking into account the time factor, cyclic analysis is used.
The operation of any technical indicator can be significantly improved if cyclic analysis is included in its structure. For example, by linking moving averages and oscillators to dominant market cycles, their performance can be optimized. The analysis of cycles also allows to increase the accuracy of the analysis of trend lines, indicating which lines are significant and which are not. In combination with the peaks and dips of the cycles, the possibilities of analyzing price models can be significantly increased. With the help of “time windows” it is possible to filter the price movement in such a way that excess signals will be cut off, and priority attention will be paid only to the moments of the most important peaks and bases of the cycles.
Prediction of the future and cycles
Can you predict the future? I can. For example, tomorrow my train will leave at exactly 10:00. The sunset tomorrow will be exactly at 19:51, and the dawn at 5:11. Do you want to bet that this is not so and my predictions will not come true? I think no. What am I really doing - predicting the future or not?
First, we really do predict the future every day. At least in the field of natural or astronomical phenomena.
Secondly, the greater accuracy of our predictions is due to the fact that there are clearly defined repeating cycles.
Nevertheless, the presence of cycles in our lives has become so familiar that we do not attach special importance to the predictions based on them. We simply project cycles into the future, assuming that they will be repeated.
But what about the idea that, in general, a person’s whole life is repeating cycles of events? He got up in the morning, went to work, worked. He came, had fun in a chat for traders, went to bed. And so day after day. But what if there are certain cycles in entrepreneurial activity? Then they must exist in the securities markets. But can there be economic cycles within a whole country? They can.
Quite a lot of literature is devoted to the cyclical nature of our whole life. For example, an excess of Atlantic salmon occurs once every 9.6 years. Every 22.2 years, a military conflict occurs in the world. Sun spots appear with an amplitude of 11.11 years. In the real estate market, the cycles are 18.33 years. In the securities market - 9.2 years.
The picture above shows the cycles of solar activity. Blue circles indicate local crises. Red - the world. Yellow - oil. Here is the link to this chart in tradingview. Judge for yourself.
The following figure will generally bring you a lot of thought:
As you can see, cycles really exist, this is an indisputable fact. It remains only to figure out how to use them.
Basic concepts of cyclic analysis
In 1970, J. Hurst published the book “The Mysterious Art of Timely Stock Market Operations”. Although the book is mainly devoted to the cycles that determine the functioning of stock markets, it represents the most complete and accessible exposition of the theory of cycles. Three years after the book was published, Siklitek Services published a cycle analysis course based on Hurst’s book. Unlike Hurst’s book, this course also covers cyclic analysis in some other areas, in particular in commodity futures markets.
The example above shows two repetitions of the price cycle. The lower point of the development of the cycle is called the base (trough), the upper - the top (crest). Note that the two waves shown in the example measure from base to base. It's just that in a cyclic analysis it is customary to measure the length of the cycles between the lower points. You can measure the distance between the peaks, but the parameters obtained in this way are considered unstable and, accordingly, not so reliable. Thus, the most common way to determine the start and end of a cycle is to measure a cyclic wave at its lowest points.
The main characteristics of the cycle are amplitude, period and phase. Amplitude measures height and is expressed in dollars, cents or points. A wave period measures the time between the lower points.
In the example below, the period is twenty days. Phase is called the temporary position of the base of the wave.
The example below shows the phase difference between two waves:
Since always at the same time several cycles develop simultaneously, phase analysis allows you to identify relationships between cycles of different lengths, as well as determine the cycle time through the lower point. If, for example, we know when a twenty-day cycle passed through the lower point (say, ten days ago), then we can easily determine when this will happen again. Once the amplitude, period and phase of the cycle are determined, it is theoretically possible to extrapolate the cycle into the future. If we can assume that the characteristics of the cycle remain more or less unchanged, then we can determine the future lower and upper points of its development. This is the basis of cyclic analysis in its simplest form.
Principles of cyclic analysis
Let's look at some of the principles that form the basis of the theory of cyclicity. The most significant are the principles of summation, harmony, synchronism and proportionality.
The principle of summation is that all price movements are a simple addition of all active cycles. The example in the figure below demonstrates that the price model at the top of the market is formed by simply adding two different cycles at the bottom of the graph:
Pay special attention to the fact that a double peak appears in the composite wave C. According to the cyclical theory, all price models are formed as a result of the interaction of two or more different cycles. Thus, the principle of summation helps to understand the logic of forecasting market development using cyclical analysis. Suppose that any price movement is the sum of cycles of varying lengths. Suppose further that each of these cycles can be isolated and measured. And finally, let's assume that each of them will continue in the future. Then you can simply continue all the cycles, projecting them into the future, and fold them again, while receiving the future market development trend. In any case, the cyclic theory speaks of such an opportunity.
The principle of harmony implies that the ratio of neighboring waves is determined by a small integer, usually "2". For example, the next smaller cycle adjacent to the twenty-day one will be a ten-day cycle - that is, two times smaller. The next ascending order will be forty-day, that is, twice as large.
The principle of synchronism is intended to explain the strong tendency of waves of various lengths to reach the base almost simultaneously. On an example, both principles are demonstrated - harmony and synchronism:
Wave B, which is located at the bottom of the graph, is half the length of wave A. Wave A includes two repetitions of the smaller wave B, demonstrating a harmonious relationship between the two waves. Note that when wave A reaches a low point, wave B also drops to the limit, demonstrating the synchronism that exists between the two waves. The principle of synchronism also means that cycles of the same length in different markets also tend to reach extremes simultaneously.
The principle of proportionality is used to describe the relationship between the period and the amplitude of the cycle. A cycle with a larger period should have a proportionally larger amplitude. The amplitude (or height) of the forty-day cycle, for example, should be approximately twice the amplitude of the twenty-day cycle.
Principles of variation and rating
There are two more principles of the theory of cyclicity that describe the functioning of cycles in more general forms. These are the principles of variation and rating.
The principle of variation is the recognition of the fact that all of the principles already mentioned (summation, harmony, synchronism and proportionality) can be called stable trends rather than rules. In real life, some “variations” have to happen and really happen.
The principle of rating is based on the assumption that, despite the peculiarities of different markets and some differences in the application of cyclical principles, there is a so-called nominal set of harmonically related cycles that are characteristic of all markets without exception. It follows that the nominal cycle duration model can be used as a starting point in the analysis of any market. The above example shows a simplified nominal model.
The dynamics of market prices are affected by various cycles. However, for prognostic purposes, only the so-called dominant cycles, which have a constant effect on prices and can be clearly defined, have real value. Most markets have at least five dominant cycles.
The correct procedure is one in which the study begins with long-term dominant cycles, the length of which reaches several years. Then they go on to analyze the average cycles of several weeks or months. And finally, ultrashort cycles, the duration of which is limited to several hours or days, are used to determine the optimal moment of entering or exiting the market, as well as to confirm the turning points of long-term cycles.
Experts in cyclic analysis do not have a single opinion on the principles of classification of cycles, as well as their length, but we still try to identify the main categories of cycles. They are as follows:
- long term cycles (long-term) (two years or more);
- seasonal cycles (seasonal) (one year);
- the main (primary);
- intermediate cycles (intermediate) (nine to twenty six weeks), and trading cycles (trading) (four weeks).
These are the main cycles, but there are others. In some markets, between the main and the trading cycles, a cycle of half the main cycle (1/2 primary cycle) is included. A trading cycle can be divided into two shorter cycles - alpha and beta, each of which takes an average of two weeks (for the first time the terms “main”, “trading”, “alpha” and “beta” were introduced by W. Bresser to describe the cycles).
However, market development is also determined by longer cycles. Probably the most famous is the fifty-four-year Kondratieff cycle. The cycle that defines economic development for a long period and named after the Russian economist Nikolai Kondratyev, who opened it in the 1920s, caused and continues to cause a lot of controversy.
Nevertheless, the cycle really has a strong influence on the development of literally all securities and commodity futures markets. In particular, the fifty-four year cycle was revealed in fluctuations in interest rates, prices for copper, cotton, wheat, stocks and wholesale prices in commodity markets. Kondratiev traced the development of his cycle from 1789 on such indicators as commodity prices, pig iron production, wages of agricultural workers in England, and so on.
In recent years, interest in the Kondratyev cycle has risen sharply again. This is explained by the fact that, according to the theory of the Russian scientist, another lowland of economic activity falls on 2010.
The combination of cycles of different lengths
According to the general rule, the long-term and seasonal cycles determine the main market development trend. When the two-year cycle of market development reaches its foundation, then prices will rise for at least one year (when measuring the cycle from the base to the top). Thus, long-term cycles affect the main direction of market movement. Market development is also subject to annual seasonal cycles, in other words, the market reaches the top or bottom at certain times of the year. For example, in grain markets, prices fall to their lowest levels during the harvest period, after which they begin to rise. Seasonal movements usually last for several months.
Of most interest is the main weekly cycle. A three to six-month main cycle is the equivalent of an intermediate trend and allows you to determine on which side of the market you should take your position. Then, to decrease, there follows a four-week trading cycle, with the help of which entry and exit points are established in accordance with the prevailing market trend. If the main trend is upward, then long positions should be opened at the bottom of the trading cycle. With a downward trend, when the cycle reaches the top, a sale should be made. You can use ten-day alpha and beta cycles for even more accurate timing of operations.
According to one of the basic rules of technical analysis, all operations should be carried out exclusively in the direction of the existing trend.Short-term price drops should be used to open long positions if the development of the market as a whole is determined by an intermediate upward trend, and vice versa, short positions should be taken with price spikes amid a general decline.
Thus, analyzing the short-term trend in order to determine the best moment to enter the market (or exit it), it is first necessary to establish the direction of the longer trend of the next level and open positions in accordance with it. The direction of development of the cycle is determined by the direction of the next ascending cycle. In other words, the direction of the short cycle can be established no earlier than the direction of the longer becomes clear.
Twenty eight day shopping cycle
There is another major short-term cycle that determines the development of most commodity markets - a twenty-eight-day trading cycle. Many markets do tend to evolve in a trading cycle that reaches its lowest point every four weeks. One of the possible explanations for such a stable cyclical pattern observed in almost all markets is the lunar cycle. In the thirties of the last century, B. Pugh studied the twenty-eight-day cycle of development of the wheat market.
The researcher concluded that the development of the lunar phases has some influence on the turns of these markets, and even made the following conclusion: wheat should be bought during the full moon, and sold at the birth of a new moon. At the same time, B. Pugh recognized that the action of the lunar phases is relatively weak and is often blocked by the influence of longer cycles or the most important events of an economic or other nature.
Whether the moon has anything to do with it or not, the average twenty-eight-day cycle still exists and explains the prevalence of many numbers used to create short-term indicators and trading systems. First, the twenty-eight-day cycle is based on the calendar structure of the month — it corresponds to four weeks. If you take into account only working days, or trading days, then it becomes already twenty days. Five-, ten- and twenty-day moving averages are very popular, as well as their derivatives - four-, nine- and eighteen-day ones.
The existence of a four-week trading cycle explains the popularity of this number and helps us understand why the “four-week rule” has been working so successfully for many years. When the market overlaps the previous maximum price value set within four weeks, the principle of cyclicality tells us that at least it has reached its lowest point and turned up the next, eight-week cycle, in ascending order.
Left and right offset
The left (or right) offset is the shift of the peaks of the cycle to the left (or right) from the ideal center. For example, a twenty-day trading cycle is measured from the bottom to the bottom. The ideal peak of this cycle, thus, is located at a distance of ten days from its beginning, or strictly in the middle. With this construction, the cycle consists of a ten-day rise in prices, followed by a ten-day fall. However, ideal cycle development is extremely rare. It should be remembered that any deviation in the cyclic development from the ideal falls on the top of the cycle, and not on the base. Therefore, the lower points of the cycles are considered more reliable parameters and are used to measure the length of the cycle.
The location of the upper points of the cycle can be different and depends on the direction of development of the next ascending cycle. If a longer trend is defined as upward, then the top of the cycle is shifted to the right of the ideal center, that is, the right shift occurs. In a downward trend, the top moves to the left of the center, causing a left shift. Thus, the right bias is a manifestation of the bull market, and the left bias is a bear market. With bull market development, price increases last longer than drops. With a bearish development, everything happens the other way around. Does this not remind you of the basic definition of a trend - with one exception: here we are talking about time, not about price.
You, of course, remember that an upward trend is defined as a series of successively increasing peaks and dips. The downtrend is a series of successively decreasing peaks and dips. In the peaks and dips of the trend, the upper and lower points of the cycle development are easily recognized. Now we can try to combine the concepts of trend and bias, as in the figure above. When peak and fall levels rise (that is, prices rise steadily), cycle peaks move to the right of the ideal center.
When the levels of peaks and dips drop (that is, prices fall steadily), the cycle goes through the peaks earlier, that is, to the left of the ideal center. Only in one case, the top of the cycle coincides with the ideal center - when there is no pronounced tendency on the market and prices move within the horizontal “trading” corridor, indicating that the forces of bulls and bears are in equilibrium.
Now let's look at the prognostic possibilities that the right and left bias possess. To begin with, even by the location of the peak of the cycle relative to the ideal center, one can fairly accurately judge the direction of market development. So, if the peak shifts to the right, that is, if the last segment of price growth in time is longer than the last segment of price decline, then we can expect that the upward trend will continue.
When the top moves to the left, this can be regarded as an advance signal of a change in trend. With regard to daily charts, it is very easy to analyze the shift of the top of the cycle - just compare the number of days during which the market went up and down, respectively. By the same principle, weekly and monthly charts can be analyzed.
For example, if the market adheres to a downtrend and the last segment of the price drop is twelve days, then the subsequent revival of the market is unlikely to last more than twelve days. Two important conclusions can be drawn from this. Firstly, if market recovery continues as the twelve-day period comes to an end, we can very likely predict the exact day that the market will turn if the downtrend is destined to resume. If the recovery goes beyond the twelve-day period, then this indicates a turning point in the trend.
Exactly the same technique is used in the analysis of weekly charts. Suppose prices are rising steadily. The distance from the bottom to the top of the last upward price movement was seven weeks. This means that any downward price adjustment or horizontal consolidation should not last longer than seven weeks. This time limit can be combined with certain price parameters. The maximum downward correction of prices is usually from 50% to 66% of previous growth.
Almost all commodity futures markets are more or less affected by annual seasonal cycles. When we talk about a seasonal cycle or a seasonal model, we mean the tendency of markets to move in a certain direction at certain times of the year.
The most striking example of such an impact is the dynamics of prices in the grain markets. Prices invariably fall during the harvest period when the maximum quantity of grain appears on the market. For example, in the soybean markets, 70% of all seasonal price highs are from April to July, and 75% of the lows are from August to November. After the maximum or minimum minimum seasonal price has been reached, prices begin to fall (or increase accordingly). Seasonal fall (or growth) usually lasts several months. Thus, knowledge of the characteristics of seasonal price dynamics is a good help in developing a trading strategy.
The reasons for seasonal effects on price dynamics, leading to peaks and bottoms at certain times of the year, are especially evident in agricultural markets. However, almost all markets are affected by seasonal factors. According to one of the most common patterns that apply to all markets, a break in the January high is a bullish signal.
Metal markets can also serve as examples of the impact of seasonal factors on price dynamics. For example, in the copper market from January-February there has been a strong steady seasonal increase in prices, which tends to reach the top in March or April. In the gold market, seasonal growth also begins in January, with prices reaching yet another base in August. Silver prices usually fall to their lowest level in January, after which they steadily rise until March.
Analysis of the frequency of seasonal market movements over the past years allows you to draw up graphs of seasonal trends. With their help, you can determine the likelihood of the manifestation of certain seasonal patterns for each month and every week of the year. By the way, the site has a great tool for identifying seasonal trends.
In some years, prices refuse to follow the expected seasonal trend, and the trader should carefully monitor the appearance of signals of this kind. The ability to notice a violation of seasonal patterns in the movement of prices as early as possible is of great importance, allowing the trader to revise the trading strategy in time. The failure of the market to follow a seasonal trend usually means that we should expect a significant price movement in the opposite direction. The opportunity to learn as soon as possible that you made the wrong move is one of the main advantages of technical analysis in general and analysis of seasonal cycles in particular.
Using cycles and technical analysis
Analysts involved in the study of market cycles emphasize that in order to confirm the feasibility of opening a particular position, the results of a cyclical analysis must be combined with the signals of other technical instruments. For example, the analyst can get an idea of when the cycle should occur using time windows or time bands, which are types of time filters that can filter out insignificant price movements.
However, after prices enter the time window, the trader must resort to more traditional technical tools that can confirm the fact of the cycle turning, thereby giving a signal to action. The choice of specific methods to determine the most favorable moments of entry and exit from the market remains with the trader who prefers to rely on his favorite, most familiar tools.
Time windows do not make any sense if they are not used in combination with specific technical signals. Among the signals that are considered the most important are breaks in trend lines postponed through closing prices, key fracture days, as well as breaks in the closing price of the level of maximum or minimum closing prices fixed during the last three days (or other units of time). For example, a buy signal at the bottom of the cycle will occur when the closing price reaches a value that exceeds the maximum closing price for the last three days (or three weeks for a weekly chart).
HAL Market Cycles Bresser uses the concept of time and price windows (they are marked with small rectangles on the charts). Timelines are based on seventy percent time bands, which are determined separately for the cycle of each length. At the same time, it is understood that in 70% of cases the rotation of the cycle will occur within such a band.
A combined analysis of price and time indicators according to Bresser involves the use of various technical methods, including determining the price reference by pause at the central point of the cycle (midcycle pause price objective) (a technique similar to determining price targets by the “measured move” method, which we already talk about described earlier), sixty-forty percent corrections of the correction length, analysis of support and resistance levels, trend lines. Bresser emphasizes the need to harmonize these techniques with the basic principles of cyclic theory.
For example, the methods of a pause at the central point of the cycle and percentages of the correction length are reliable only if, firstly, the length of the analyzed cycle coincides with the prescribed one, and secondly, if the trend continues, expressed by the next ascending cycle .
Trendlines are most reliable when they connect the tops or bottoms of cycles of the same length. For example, trend lines need to be constructed so that they connect the upper or lower points of two trading cycles or adjacent alpha or beta cycles, which, as a rule, have the same length. A break in a trend line connecting cycles of the same length is a signal that a rotation of the next ascending cycle has occurred.
So, if the market crosses a downtrend built through the tops of the alpha and beta cycles, this means that a longer trading cycle has reached its base.
Using cycles and oscillators
One of the most interesting areas for sharing cycles and other more traditional methods of technical analysis is to link oscillators to current cycles. Experts believe that the efficiency of oscillators can be significantly increased if the time periods used to calculate them are determined taking into account the length of the cycles operating on the market.
A book on the use of the Hal methodology, sponsored by The Hal Blue Book, WJ Bressert and JH Jones, describes in detail how market development cycles combine with overbought-oversold index and pace index (momentum) . Both oscillators are taken from the book by Larry Williams, “How I made a million dollars last year by playing in the commodity futures market,” published in 1973. The overbought-oversold index is a modification of the% R Williams oscillator, and the second oscillator is a simple tempo index that can be built by measuring the price difference between two time periods.
The main thing is to bind the oscillator calculation period to the length of the cycles. To begin with, we determine the number of working days that make up the trading cycle. Assume that the average length of a trading cycle is 28 calendar days. However, of these working days - only twenty. When we try to identify the turns of a cycle using an oscillator, we need to take a period equal to half the length of this cycle to calculate it. In the example below, we used a period of ten days:
The Hal method involves constructing three oscillators based on three cycles of different lengths: trading (twenty days), alpha-beta (ten days) and long (usually twice as long as the trade, i.e. forty-day). Of course, we are talking about cycles of averaged length, and it is always necessary to take into account the actual cycle length in each individual market. When constructing oscillators in each of the three cases, a period corresponding to half the cycle of each type is taken. In our example, these will be the following values: 20, 10 and 5:
Oscillators built on the basis of these three values can be delayed on one or on different graphs. The interaction of oscillators of various lengths can provide traders with very valuable information.
Another way to combine oscillators with cycles is to use time bands as a filter. In this case, it is especially necessary to carefully monitor the oscillator for signs of the top or bottom when prices enter the time band, indicating that the cycle is approaching its upper or lower point.
The principle of “linking” oscillators to the length of cycles can be used in the construction of almost any type of oscillator by inserting the corresponding value into their formulas.
Today we examined in detail the opportunities that the trader provides analysis of time cycles. You do not need to be a specialist in the field of cycle analysis in order to see the advantages that we get, including a temporary measurement in our forecasts. To do this, as we found out, is quite simple. In combination with cycle analysis, for example, you can use the technical analysis methods that you constantly use. Experts in cyclic analysis believe that only with the help of cycles can you see in advance which direction the market will go. It is true or not, but one thing is certain: using the analysis of cycles it is really possible to increase the efficiency of market forecasting.
The basis of the cycle in the analysis is considered more reliable than the top, and therefore cyclic changes are measured from the bottom to the bottom. That is why the analyst pays attention primarily to the foundations of the cycles. Unfortunately, this leads to the fact that the analyst has the obsession to “catch the bottom” of the cycle and play on the rise instead of calmly following the downward trend.
Knowing this particularity of cyclical analysis, it is best to probably pay less attention to cycles during the bearish phases of market development and turn to them again when prices begin to follow a confirmed bullish trend.